基于印度手语的手势识别软件

Sanket Kadam, Aakash Ghodke, Sumitra Sadhukhan
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引用次数: 4

摘要

手势是与智障群体沟通的强大环境。它对于连接人和电脑很有用。在聋人与普通人交流信息的公共场所,可以看到该系统的扩展潜力。在本文中,我们提供了一个用印度手语(ISL)连续识别手势的系统,该系统使用双手做出每个手势。手势识别仍然是一项艰巨的任务。我们尝试使用密钥下载方法来解决这个问题。这些关键提示对于将手语手势分解为字符顺序以及删除不支持的框架非常有用。在分裂齿轮断裂后,每个字符都被视为一个单一而独特的手势。预处理手势使用直方图(OH)和主成分分析(PCA)来降低OH后得到的特征的维数。实验是在我们的实时ISL数据集上进行的,该数据集是使用现有的相机创建的。
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Hand Gesture Recognition Software Based on Indian Sign Language
Hand gestures are a pwerful environment for communicating with communities with intellectual disability. It is useful for connecting people and computers. The expansion potential of this system can be known in public places where deaf people are communicating with ordinary people to send messages. In this article, we have provided a system of recognizing gestures continuously with the Indian Sign Language (ISL), which both hands are used to make every gesture. Gesture recognition continues to be a daunting task. We tried to fix this problem using the key download method. These key tips are useful for breaking down the sign language gestures into the order of the characters, as well as deleting unsupported frameworks. After the splitting gear breaks each character is regarded as a single and unique gesture. Pre-processing gestures are obtained using histogram (OH) with PCA to reduce the dimensions of the traits obtained after OH. The experiments were performed on our live ISL dataset, which was created using an existing camera.
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